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来源声明： http://blog.minidx.com/2008/01/27/446.html
先保存下来，以备后面研究，现在还看不懂！
哈希算法将任意长度的二进制值映射为固定长度的较小二进制值，这个小的二进制值称为哈希值。哈希值是一段数据唯一且极其紧凑的数值表示形式。如果散列一段明文而且哪怕只更改该段落的一个字母，随后的哈希都将产生不同的值。要找到散列为同一个值的两个不同的输入，在计算上是不可能的，所以数据的哈希值可以检验数据的完整性。
链表查找的时间效率为O(N)，二分法为log2N，B+ Tree为log2N，但Hash链表查找的时间效率为O(1)。
设计高效算法往往需要使用Hash链表，常数级的查找速度是任何别的算法无法比拟的，Hash链表的构造和冲突的不同实现方法对效率当然有一定的影响，然 而Hash函数是Hash链表最核心的部分，下面是几款经典软件中使用到的字符串Hash函数实现，通过阅读这些代码，我们可以在Hash算法的执行效率、离散性、空间利用率等方面有比较深刻的了解。
下面分别介绍几个经典软件中出现的字符串Hash函数。
●PHP中出现的字符串Hash函数
static unsigned long hashpjw(char *arKey, unsigned int nKeyLength) { unsigned long h = 0, g; char *arEnd=arKey+nKeyLength; while (arKey < arEnd) { h = (h << 4) + *arKey++; if ((g = (h & 0xF0000000))) { h = h ^ (g >> 24); h = h ^ g; } } return h; }
●OpenSSL中出现的字符串Hash函数
unsigned long lh_strhash(char *str) { int i,l; unsigned long ret=0; unsigned short *s; if (str == NULL) return(0); l=(strlen(str)+1)/2; s=(unsigned short *)str; for (i=0; i ret^=(s[i]<<(i&0x0f)); return(ret); } /* The following hash seems to work very well on normal text strings * no collisions on /usr/dict/words and it distributes on %2^n quite * well, not as good as MD5, but still good. */ unsigned long lh_strhash(const char *c) { unsigned long ret=0; long n; unsigned long v; int r; if ((c == NULL) || (*c == ‘\0‘)) return(ret); /* unsigned char b[16]; MD5(c,strlen(c),b); return(b[0]|(b[1]<<8)|(b[2]<<16)|(b[3]<<24)); */ n=0x100; while (*c) { v=n|(*c); n+=0x100; r= (int)((v>>2)^v)&0x0f; ret=(ret(32-r)); ret&=0xFFFFFFFFL; ret^=v*v; c++; } return((ret>>16)^ret); }
●MySql中出现的字符串Hash函数
#ifndef NEW_HASH_FUNCTION /* Calc hashvalue for a key */ static uint calc_hashnr(const byte *key,uint length) { register uint nr=1, nr2=4; while (length--) { nr^= (((nr & 63)+nr2)*((uint) (uchar) *key++))+ (nr << 8); nr2+=3; } return((uint) nr); } /* Calc hashvalue for a key, case indepenently */ static uint calc_hashnr_caseup(const byte *key,uint length) { register uint nr=1, nr2=4; while (length--) { nr^= (((nr & 63)+nr2)*((uint) (uchar) toupper(*key++)))+ (nr << 8); nr2+=3; } return((uint) nr); } #else /* * Fowler/Noll/Vo hash * * The basis of the hash algorithm was taken from an idea sent by email to the * IEEE Posix P1003.2 mailing list from Phong Vo (kpv@research.att.com) and * Glenn Fowler (gsf@research.att.com). Landon Curt Noll (chongo@toad.com) * later improved on their algorithm. * * The magic is in the interesting relationship between the special prime * 16777619 (2^24 + 403) and 2^32 and 2^8. * * This hash produces the fewest collisions of any function that we‘ve seen so * far, and works well on both numbers and strings. */ uint calc_hashnr(const byte *key, uint len) { const byte *end=key+len; uint hash; for (hash = 0; key < end; key++) { hash *= 16777619; hash ^= (uint) *(uchar*) key; } return (hash); } uint calc_hashnr_caseup(const byte *key, uint len) { const byte *end=key+len; uint hash; for (hash = 0; key < end; key++) { hash *= 16777619; hash ^= (uint) (uchar) toupper(*key); } return (hash); } #endif
Mysql中对字符串Hash函数还区分了大小写
●另一个经典字符串Hash函数
unsigned int hash(char *str) { register unsigned int h; register unsigned char *p; for(h=0, p = (unsigned char *)str; *p ; p++) h = 31 * h + *p; return h; }
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原文地址：http://www.cnblogs.com/mingaixin/p/5247653.html
